Title: Task scheduling optimisation algorithm based on load balance under the cloud computing environment

Authors: Shibiao Mu

Addresses: Yiwu Industrial and Commercial College, Yiwu, 322000, China

Abstract: In order to achieve an optimal task scheduling scheme with the constraint of load balance in cloud computing platform. We utilise the CloudSim simulator to construct the cloud computing environment, and CloudSim contains three components: 1) CloudSim core simulation engine; 2) CloudSim basic structure; 3) user codes. Afterwards, we propose a novel load balancing oriented task scheduling optimisation algorithm based on genetic algorithm, and task assignment results are obtained through analysing gene values of chromosomes. In order to ensure convergence rate in genetic algorithm, we design the fitness function by integrating computation time and computation cost together. Furthermore, we design adaptive crossover and mutation operations to promote the search efficiency. Finally, we conduct an experiment to demonstrate the performance of the proposed algorithm. The experimental results show that the proposed algorithm can achieve the goal of high level of load balance with lower calculation time and cost.

Keywords: load balancing; task scheduling; cloud computing; genetic algorithm; fitness function.

DOI: 10.1504/IJADS.2018.090932

International Journal of Applied Decision Sciences, 2018 Vol.11 No.2, pp.210 - 222

Received: 21 Jun 2017
Accepted: 11 Oct 2017

Published online: 20 Feb 2018 *

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